high performance computing on graphics processing units: hgpu.org

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Nested Data-Parallelism on the GPU

Lars Bergstrom, John Reppy

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Tags: Algorithms, Compilers, Computer science, CUDA, Data parallelism, nVidia, Package, Programming Languages, Tesla C2050

March 31, 2012 by hgpu

Adaptive Input-aware Compilation for Graphics Engines

Mehrzad Samadi, Amir Hormati, Mojtaba Mehrara, Janghaeng Lee, and Scott Mahlke

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Tags: Compiler, CUDA, GPU, nVidia, nVidia GeForce GTX 285, Optimization, Portability, Streaming, Tesla C2050

March 31, 2012 by Moaddeli

A Highly Parallel Reuse Distance Analysis Algorithm on GPUs

Huimin Cui, Qing Yi, Jingling Xue, Lei Wang, Yang Yang, Xiaobing Feng

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Tags: Algorithms, Computer science, CUDA, Memory model, nVidia, Tesla C2050

March 30, 2012 by hgpu

Optimized Strategies for Mapping Three-dimensional FFTs onto CUDA GPUs

Jing Wu, Joseph JaJa

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Tags: Algorithms, Computer science, CUDA, FFT, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Performance, Tesla C1060, Tesla C2050

March 30, 2012 by hgpu

A Performance Analysis Framework for Identifying Potential Benefits in GPGPU Applications

Jaewoong Sim, Aniruddha Dasgupta, Hyesoon Kim, and Richard Vuduc

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Tags: Analytical model, CUDA, GPGPU architecture, nVidia, Performance benefit prediction, Performance prediction, Tesla C2050

March 30, 2012 by Moaddeli

Scheduling Tasks over Multicore machines enhanced with Accelerators: a Runtime System’s Perspective

Cedric Augonnet

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Tags: Cell processor, Computer science, CUDA, Databases, nVidia, nVidia Quadro FX 4600, nVidia Quadro FX 5800, Task scheduling, Tesla C2050, Tesla M2070, Tesla S1070, Thesis

March 29, 2012 by hgpu

Auto-tuning a High-Level Language Targeted to GPU Codes

Scott Grauer-Gray, Lifan Xu, Robert Searles, Sudhee Ayalasomayajula, John Cavazos

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 9800 GT, nVidia GeForce GTX 280, OpenCL, Optimization, Performance, Programming techniques, Stereo vision, Tesla C2050

March 28, 2012 by hgpu

Massively Parallel Localization of Pulsed Signal Transitions Using a GPU

Vinitha Khambadkar, Lee Barford, Frederick C. Harris, Jr.

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Tags: Algorithms, CUDA, nVidia, nVidia GeForce GTX 275, nVidia GeForce GTX 480, Signal processing, Tesla C2050

March 26, 2012 by hgpu

Hierarchical N-body simulations with auto-tuning for heterogeneous systems

Rio Yokota, Lorena A. Barba

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Tags: Algorithms, CUDA, Heterogeneous systems, Mathematical Software, N-body simulation, Numerical Analysis, nVidia, nVidia GeForce GTX 590, Physics, Tesla C2050

March 22, 2012 by hgpu

Shallow water simulations on multiple GPUs

Martin Lilleeng Saetra, Andre Rigland Brodtkorb

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Tags: CUDA, Fluid dynamics, nVidia, nVidia GeForce GTX 480, Tesla C2050, Tesla S1070

March 21, 2012 by hgpu

Enabling Fast, Noncontiguous GPU Data Movement in Hybrid MPI+GPU Environments

John Jenkins, Pavan Balaji, James Dinan, Nagiza F. Samatova, Rajeev Thakur

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Tags: Computer science, CUDA, MPI, nVidia, Performance, Programming Languages, Programming techniques, Tesla C2050

March 18, 2012 by hgpu

Performance analysis and optimization of the OP2 framework on many-core architectures

M.B. Giles, G.R. Mudalige, Z. Sharif, G. Markall, P.H.J. Kelly

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Tags: Benchmarking, Computer science, CUDA, Fluid dynamics, nVidia, OpenMP, Optimization, Package, Performance, Tesla C2050

March 15, 2012 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

See all packages

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high performance computing on graphics processing units: hgpu.org

Nested Data-Parallelism on the GPU

Adaptive Input-aware Compilation for Graphics Engines

A Highly Parallel Reuse Distance Analysis Algorithm on GPUs

Optimized Strategies for Mapping Three-dimensional FFTs onto CUDA GPUs

A Performance Analysis Framework for Identifying Potential Benefits in GPGPU Applications

Scheduling Tasks over Multicore machines enhanced with Accelerators: a Runtime System’s Perspective

Auto-tuning a High-Level Language Targeted to GPU Codes

Massively Parallel Localization of Pulsed Signal Transitions Using a GPU

Hierarchical N-body simulations with auto-tuning for heterogeneous systems

Shallow water simulations on multiple GPUs

Enabling Fast, Noncontiguous GPU Data Movement in Hybrid MPI+GPU Environments

Performance analysis and optimization of the OP2 framework on many-core architectures

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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